Google Cloud Professional Data Engineer — Question 243

You are administering a BigQuery on-demand environment. Your business intelligence tool is submitting hundreds of queries each day that aggregate a large (50 TB) sales history fact table at the day and month levels. These queries have a slow response time and are exceeding cost expectations. You need to decrease response time, lower query costs, and minimize maintenance. What should you do?

Answer options

• A. Build authorized views on top of the sales table to aggregate data at the day and month level.
• B. Enable BI Engine and add your sales table as a preferred table.
• C. Build materialized views on top of the sales table to aggregate data at the day and month level.
• D. Create a scheduled query to build sales day and sales month aggregate tables on an hourly basis.

Correct answer: C

Explanation

The correct answer is C because building materialized views allows for pre-computed and stored results of the aggregations, which significantly speeds up query response times and reduces costs associated with querying large datasets. The other options either do not provide the same efficiency, like authorized views (A) and BI Engine (B), or involve continuous maintenance and may not optimize costs effectively as with scheduled queries (D).